Photographic color distortion and color banding in digital imaging are induced by the interaction between image patterns and image color sensor patterns. These undesirable effects are a consequence of having repetitive image features on order of the size of the individual pixel sensors and from sharp edges representing an abrupt change in color. Since real-world pattern spacing never quite matches the digital sensor patterns, the color that is overweighted will vary spatially through the picture in correspondence to how out of phase the two patterns are from each other. Typically, this causes the colors to cycle and results in rainbow-like color distortions and other artifacts in the displayed digital image, often referred to as moiré effects.
There are several approaches to resolving color moiré effects: computational post-processing, sensor array modifications, and specialty filters. Of these approaches, digital computational post-processing methods include using software such as the ADOBE PHOTOSHOP program, requiring that a user manually resolve the color moiré through digital filters and selection, an often time-consuming and cumbersome approach that can require a high degree of expertise and results in a degraded image. Performing post-processing within the camera requires a powerful microprocessor and large amounts of working memory, contrary to low-cost and fast picture taking. It also requires assumptions to be made regarding the nature of the incoming image which may not hold true.
Modifying the sensor array to solve the moiré effects is also a viable, although expensive, approach and is not guaranteed to resolve the effects. One such approach involves a hexagonal sensor arrangement, rather than a square arrangement, which appears to be less sensitive to color moiré. However, instead of eliminating the moiré effects, the hexagonal sensor arrangement changes the patterns to which it is sensitive, causing other undesirable effects. Yet another approach involves a CMOS-based sensor that senses red green and blue at each pixel without relying on color filters. This approach uses a three-level sensor, in the direction of the incoming light signal, that takes advantage of the different penetration depths of light in the red, green, and blue wavelengths. However, this approach can result in high manufacturing costs and difficult reliability issues, requiring an integrated circuit having a trilayer stack of transistors, each of which operates within very tight specifications.
Other approaches involve the use of specialty filters to optically solve the problem, including optical low pass filters, often referred to as blur filters. A conventional optical solution uses liquid crystalline polymers or a stack of inorganic plates, for example quartz plates, each of which have been ground in such a way as to expose the asymmetry of the quartz axis and create a birefringent walk-off plate stack. Typically, the walk-off plate laterally displaces one state of polarization from another. These plates are stacked in different orientations to obtain the desired blur pattern and are placed within the optical path between a lens and image sensor. The plate stack is usually two or more millimeters in thickness, typically far too thick to be included in mobile phones or personal digital assistants having digital cameras. Also, the quartz plates can be expensive for certain implementations and tend to break easily, making them difficult to handle and not particularly well-suited to mobile devices.
Yet another approach to the making of a blur filter uses a diffraction grating. A plate with an array of structures is placed in the optical path between the lens and the sensor. The diffraction grating modifies the phase relationships in the incoming light and creates a pattern of constructive and destructive interference. The interference pattern effectively spreads a portion of the incoming light to higher angles. For example, a collimated beam of light that would otherwise appear as a concentrated spot across a small angular domain is spread into several spots over a wider area. Blur filters of this type have been described, for example, in U.S. Pat. No. 4,998,800.
An undesirable effect occurring in image sensors includes anomalous variations in intensity resulting from diffraction of the incoming light signal, and arising, for example, from higher order diffraction peaks. One approach to reduce these anomalies, including color anomalies, involves using “blazed transmission grating” equations to find pitches that reduce or eliminate the anomalies. The difficulty with this approach is that for small pitches, the solutions only optimize for single wavelengths; thus, diffraction can be eliminated for the color red, for example, but may still be severe for the color blue. The blazed grating equations are less sensitive to wavelength for large pitches, allowing a reasonable optimization for all visible wavelengths. However, with large pitches (e.g., 250 microns) the groove depth becomes deeper (e.g., 26 microns) and begins to project onto the sensor imaging surface, an undesirable situation.